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Community structure in the phonological network

Overview of attention for article published in Frontiers in Psychology, January 2013
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

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1 blog
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7 X users
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3 Google+ users

Citations

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71 Dimensions

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43 Mendeley
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Title
Community structure in the phonological network
Published in
Frontiers in Psychology, January 2013
DOI 10.3389/fpsyg.2013.00553
Pubmed ID
Authors

Cynthia S. Q. Siew

Abstract

Community structure, which refers to the presence of densely connected groups within a larger network, is a common feature of several real-world networks from a variety of domains such as the human brain, social networks of hunter-gatherers and business organizations, and the World Wide Web (Porter et al., 2009). Using a community detection technique known as the Louvain optimization method, 17 communities were extracted from the giant component of the phonological network described in Vitevitch (2008). Additional analyses comparing the lexical and phonological characteristics of words in these communities against words in randomly generated communities revealed several novel discoveries. Larger communities tend to consist of short, frequent words of high degree and low age of acquisition ratings, and smaller communities tend to consist of longer, less frequent words of low degree and high age of acquisition ratings. Real communities also contained fewer different phonological segments compared to random communities, although the number of occurrences of phonological segments found in real communities was much higher than that of the same phonological segments in random communities. Interestingly, the observation that relatively few biphones occur very frequently and a large number of biphones occur rarely within communities mirrors the pattern of the overall frequency of words in a language (Zipf, 1935). The present findings have important implications for understanding the dynamics of activation spread among words in the phonological network that are relevant to lexical processing, as well as understanding the mechanisms that underlie language acquisition and the evolution of language.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 5%
Italy 1 2%
Unknown 40 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 23%
Student > Master 7 16%
Researcher 5 12%
Professor 4 9%
Professor > Associate Professor 4 9%
Other 9 21%
Unknown 4 9%
Readers by discipline Count As %
Psychology 13 30%
Linguistics 10 23%
Computer Science 4 9%
Engineering 3 7%
Agricultural and Biological Sciences 2 5%
Other 5 12%
Unknown 6 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 18. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 June 2014.
All research outputs
#2,115,134
of 25,734,859 outputs
Outputs from Frontiers in Psychology
#4,292
of 34,768 outputs
Outputs of similar age
#19,432
of 290,917 outputs
Outputs of similar age from Frontiers in Psychology
#187
of 967 outputs
Altmetric has tracked 25,734,859 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 34,768 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.4. This one has done well, scoring higher than 87% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 290,917 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 967 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.